Amel F. Tashani & Sarah A. Aggag

Genetic diversity and wood anatomy of pines in Al-Jabal Al-Akhdar, Libya: A DNA barcoding approach

Résumé

Diversité génétique et anatomie des pins d’Al-Jabal Al-Akhdar, Libye : une approche par code-barres ADN

Description du sujet. La distribution géographique, les occurrences historiques et l’activité humaine font partie des variables qui influencent la diversité génétique des espèces de Pinus. Comprendre ces schémas est essentiel dans les efforts de conservation et pour adapter les stratégies de gestion forestière aux changements climatiques.

Objectifs. Les niveaux contrastés de diversité génétique entre les espèces de Pinus soulignent l’importance d’approches spécifiques à chaque espèce dans les programmes de conservation et de gestion. Le code-barres ADN constitue une méthode efficace pour identifier diverses espèces végétales à travers les taxons et les écosystèmes.

Méthode. Dans cette étude, les espèces de Pinus ont été classifiées et leur distribution géographique a été étudiée dans la région d’Al-Jabel Al-Akhdar où elles poussent à différentes altitudes dans des forêts naturelles et reboisées. La composition anatomique du bois a été examinée, notamment l’épaisseur des parois des trachéides, l’épaisseur du bois final, la surface du parenchyme des rayons, le nombre de canaux résinifères, la hauteur des rayons et la longueur des fibres. De plus, le code-barres ADN a été réalisé à l’aide des amorces rbcL.

Résultats. Les résultats de l’examen en coupe transversale du bois des espèces de Pinus ont montré des différences significatives entre les espèces. Cependant, la surface du parenchyme des rayons ne présentait pas de différences significatives entre elles. Les régions chloroplastiques rbcL ont été utilisées comme marqueurs de code-barres pour identifier 10 plants de Pinus. Les résultats soulignent la nécessité de disposer d’une bibliothèque de référence avancée de codes-barres ADN couvrant un large éventail d’espèces pour une identification précise des espèces.

Conclusions. Cette étude ne fournit pas seulement des éclaircissements sur la diversité et la taxonomie du Pinus mais elle contribue également à la conservation continue des ressources en Pinus et soutient la gestion durable des ressources dans la région. La technologie du code-barres ADN est essentielle pour les études de taxonomie et de biodiversité car elle permet une identification rapide et précise des espèces forestières.

Abstract

Description of the topic. Geographical distribution, historical occurrences, and human activity are some of the variables that affect the genetic diversity of Pinus species. Understanding these patterns is critical for conservation efforts and for adapting forest management strategies to climate change.

Objectives. The contrasting levels of genetic diversity among Pinus species underscore the importance of species-specific approaches in conservation and management programs. DNA barcoding is an effective method for identifying diverse plant species across taxa and ecosystems.

Method. In this study, Pinus species were classified, and their geographical distribution was studied in the Al-Jabel Al-Akhdar region, growing at different altitudes in natural forests and afforested. The anatomical composition of the wood was examined, including tracheid wall thicknesses, latewood thickness, ray parenchyma area, number of resin ducts, ray height, and fiber length. Additionally, DNA barcoding was conducted using rbcL primers.

Results. The results of the cross-sectional examination of the wood of Pinus species showed significant differences among the species. However, the ray parenchyma area showed no significant differences among the species. Chloroplast rbcL regions were used as barcode markers to identify 10 Pinus plants. The results highlight the need for an advanced DNA barcode reference library with broad species coverage for accurate species identification.

Conclusions. This study not only provides insights into the diversity and taxonomy of Pinus but also contributes to the ongoing conservation of Pinus resources and supports sustainable resource management in the region. DNA barcoding technology is critical for taxonomy and biodiversity studies because it allows rapid and accurate species identification in forests.

Tabla de contenidos

Received 6 January 2025, accepted 8 October 2025, available online 26 November 2025.

This article is distributed under the terms and conditions of the CC-BY License (http://creativecommons.org/licenses/by/4.0)

1. INTRODUCTION

1Al-Jabel Al-Akhdar, located in northeastern Libya, is a region characterized by its unique geological, hydrological, and ecological features. The region boasts a diverse flora, with studies identifying 317 vascular plant taxa, including many endemic species. The ecological studies highlight the Mediterranean plant communities, which are crucial for maintaining local biodiversity and ecological balance (Alaib et al., 2017). Taxonomy is concerned with the definition and classification of all plants found on land and in water to date (Vidakovic, 1991). The oldest known classification system is the industrial classification of Theophrastus, which divided plants into three groups: trees, shrubs, and grasses. The second period developed in the 16^th century, when the Italian botanist Andrea Cesalpino classified plants according to their fruits and seeds. The Swedish botanist Carl von Linné invented the binomial nomenclature system, while Charles Darwin developed basic concepts in his book On the Origin of Species (Vidakovic, 1991). Most pine species are found in the northern hemisphere, with fossilized conifers found in Asia, the Soviet Union, and the west coasts of France and the United States. The pine genus has been classified by many scientists, with key factors based on the anatomical and phenotypic characteristics of the needle. In addition, the anatomical properties of pine wood are of great importance in classifying the genus pine through the identification of many traits. The presence of tracheids is the most important one (Ickert-Bond, 2001). The classification of conifers in the Al-Jabal Al-Akhdar region-east of Libya has been studied using phenotype and needle anatomy characters, and an identification key has been developed based on these characters (Tashani & Ali, 2021).

2The pine family, known as Pinaceae, comprises a diverse range of species found primarily in the northern hemisphere. This family is characterized by a complex evolutionary history involving significant gene flow and hybridization events among its members. Phylogenetic relationships within Pinaceae have been reconstructed using advanced genomic techniques, revealing intricate patterns of divergence and admixture among different pine species (Jiang et al., 2024). In Libya, about five pine species grow in the Al-Jabal Al-Akhdar region. Pinus halepensis L. is a small to medium sized tree with a trunk diameter of 17.73 cm. The bark is orange red in color, of considerable thickness, and with a distinctive fissured texture. The needles are slender yellowish-green, and the cones are narrow and conical. The seeds are 6 mm long, have a 2 cm wing, and are dispersed by wind (Houminer et al., 2022; Harfouch et al., 2003). It currently grows well in the forests of Shehat, Sidi Al-Hamri, Mador Al-Ziton, Marawa-Qandula, Ghout Al-Sultan, Tacness, Slanta, Bilang, and Ras Al-Hilal (Wadi Morcos), where it is planted as trees and shelterbelts, alone or mixed with Pinus pinea L., Pinus brutia and Italian cypress, Pinus brutia Ten. The tree is characterized by its conical shape, dense bark, and rectangular buds. The foliage consists of dark green, thin, serrated needles, while the flowers are produced in inflorescences. The cones are oval and have no stalk, while the seeds are brown to black in color. This species is found in the form of shelterbelts in the Gharika site of the Al-Jabal Al-Akhdar region at an altitude of 780 m (Zunni & Bayoumi, 2006). Pinus pinea grows in the Wardama site at an altitude of 625 m. It is also spread in the Al-Rajma forests in Al-Jabal Al-Akhdar region. The tree was characterized by a height of 4.8 m and a diameter of 30 cm, exhibiting a circular crown morphology. Its bark is reddish-brown. The cones are oval or spherical, and the seeds are large, measuring 1.750 cm in length, with a reduced wing that separates quickly (Tashani & Ali, 2021). Pinus massoniana var. massoniana is a tree characterized by a narrow conical crown, thick reddish-brown bark, and dark green needles. The dry weight of 100 needles was 10.1 g. The tree produces large, conical cones. The seeds are large, dark gray, and mottled (Eckenwalder, 2009; Farjon, 2010). In the Al-Jabal Al-Akhdar region, it grows in the Fayidia site, which is at an altitude of 767 m. Pinus heldreichii H.Christ is a tree that reaches a length of 6.8 m and a diameter of 33.3 cm. It has a broad and spreading crown and a dark gray to black bark. The needles are dark green and grow in two fascicles, measuring 14.5 cm in length. The cones are 8.33 cm long and 3.58 cm wide, have no petiole, and are conical in shape (Vendramin et al., 2008).

3To effectively identify and understand the relationships among these diverse Pinus species, analysis of robust molecular approaches is necessary. In this context, DNA barcoding emerges as a pivotal technology. The objective of DNA barcoding is to achieve rapid and accurate species identification by sequencing a short DNA sequence or a few DNA regions (Li et al., 2011). However, the amplification and sequencing of universal nuclear gene primers across different angiosperm taxa is a major challenge. The use of DNA barcodes derived from chloroplast genes is a common practice in plant phylogenetic studies. The rbcL (ribulose bisphosphate carboxylase/oxygenase large subunit) locus has been shown to be a valuable tool for comparative analysis at the family and genus level. This marker has been extensively studied in the plastid genome, with broad representation from all major groups and a substantial number of sequences available in GenBank (Newmaster et al., 2006). A substantial body of evidence suggests that rbcL should be used as a core barcode marker for the molecular identification of land plants (Hollingsworth et al., 2009; Li et al., 2011). In addition to selecting appropriate DNA barcode fragments, it is also essential to collect a significant number of individuals from diverse populations within a species to establish a comprehensive reference database that can be universally applied (Bolson et al., 2015; Guo et al., 2015). The selection of rbcL as a barcode marker for Pinus species is based on the complementary and unique characteristics of this marker. rbcL is recognized for higher variability and resolving power at the species level (Ismail et al., 2020) and exhibits greater universality and ease of amplification across a wide range of plant taxa (Nurhasanah & Papuangan, 2019).

4Nevertheless, the complicated physical characteristics of the genus and the considerable intraspecific variability have made the accurate identification of Pinus species challenging. The similarity of morphological traits, including leaf morphology and stem pigmentation between closely related species can lead to misidentification and a subsequent misunderstanding of their ecological functions. Despite the importance of the encyclopedia of Libya's plants and the valuable information that it contains about the plant factions in Libya, it lacks mention of the pine species that are widespread in Libya, especially in the Al-Jabal Al-Akhdar region where only P. halepensis and P. canariensis were noted. Therefore, the aim of this research is to ensure that conifer species are classified on the basis of wood anatomy and genetic characteristics.

2. MATERIALS AND METHODS

2.1. The study area

5The Al-Jabel Al-Akhdar region (JAR) is located between longitude 32° and 33°N and 20° to 23°E. The region spans approximately 360 km in length and 60 km in width from the seashore (Figure 1).

6Figure 1. Location map of the study area – Carte de localisation de la zone d’étude

2.2. Plant materials

7Needle samples of P. halepensis, P. brutia, P. pinea, P. massoniana var.massoniana, and P. heldreichii (Figure 2) were collected from the Al-Jabel Al-Akhdar region. For each species included in the study, we selected 10 mature and healthy pine trees from various natural growth sites. Within each site, trees were selected in a single row, spaced approximately 20 m apart. This spacing was maintained to minimize potential environmental interference. Needles were randomly collected from well-isolated canopy parts at 1 m ground level from each tree. After collection, needle samples were immediately stored at -80 °C until further use.

Figure 2. Trees of pine species under study– Espèces de pin étudiées.

A. Pinus halepensis; B. Pinus brutia; C. Pinus pinea; D. Pinus massoniana var.massoniana; E. Pinus heldreichii.

2.3. DNA isolation, amplification, and sequencing

8One gram of needle tissue was frozen in liquid nitrogen and homogenized using the CTAB (cetyl-tetramethyl ammonium bromide) method, according to Doyle (1990). Quantification of total DNA was performed using a Thermo Fisher Scientific Inc. NanoDrop 2000 Spectrophotometer Version 1.4.1. The DNA barcoding gene ribulose 1,5-biphosphate carboxylase (rbcL) was performed by Sigma-Aldrich Company, GATC Company (Germany): rbcL -F: 5’-TGT CAC CAC AAA CAG AAC TAA AGC-3’ and rbcL -R: 5,-GTA AAA TCA AGT CCA CCR CG-3’ (Tashani & Aggag, 2020). PCR amplifications were performed in 20 µl: 10 μl PCR master mix (Promega GoTaq® Green), 4 μl H₂O, 2 µl of the forward primer (10 µM), 2 µl of the reverse primer (10 µM), and 2 μl template DNA (50 ng). Reactions were optimized according to the recommended protocol of 95 °C for 3 min, followed by 35 cycles of denaturation at 95 °C for 30 s, annealing at 54 °C for 30 s and extension at 68° C for 40 s, and final extension at 68 °C for 6 min and 16 °C for 2 min. The PCR products were separated by agarose gel electrophoresis (1% agarose) at 80 V for 50 min (Tashani & Aggag, 2020).

2.4. DNA barcode analysis

9The resulting PCR product was excised from the gel and purified using a MEGAquick-spin™ (INtRON) total fragment DNA purification kit. The gel-purified DNA bands were sequenced on an automated sequencer using the Sanger method by Macrogene Company (Korea). The generated sequences were deposited at the National Center for Biotechnology Information (NCBI) and the basic local alignment search tool (BLAST) network service (https://blast.ncbi.nlm.nih.gov/Blast.cgi) (S1) was used. The alignment process was conducted manually, with the incorporation of criteria that considered secondary structures and mutational mechanisms. This was done to provide guidance for the strategic placement of gaps, as outlined by Kelchner (2000).

2.5. Genetic diversity analysis

10The sequences obtained were also subjected to analysis to determine the average AT% and GC% nucleotide compositions for the rbcL marker. A comprehensive investigation into genetic diversity was conducted using the MEGA11 program (Tamura et al., 2021), with a particular focus on segregating sites and nucleotide diversity across the five sequences. Subsequently, the Tajima's D test was applied to assess deviations from neutrality, thereby providing valuable information about the demographic history and evolutionary processes within the studied Pinus species.

2.6. Tree-building method

11We used MEGA 11 program, a tree-building method (Tamura et al., 2021) to construct a Neighbour-Joining (NJ) tree for the rbcL marker. The ratio of successfully identified species from all sampled species was calculated as the proportion of species that were discriminated. The sequence alignments were compared together with other Pinus species available in the GenBank database (http://www.ncbi.nlm.nih.gov).

2.7. Wood anatomy and morphometric studies

12Wood anatomy properties. Ten trees of each species at different elevations were selected. Two-inch discs (1 × 1 × 3 cm) were prepared in accordance with ISO 13061-14 (2016) and taken from each pine tree. Blocks were cut into 200-micrometer-thick transverse, tangential, and radial sections using a sliding microtome.

13Fiber length. The separation of individual wood fibers was performed using Franklin’s (1945) method, through which a wood specimen with the dimensions of 15 × 10 × 2 mm was saturated in a mixture (1:1) of acetic acid and oxygenized water in test tubes. Afterwards, the specimens were kept in an oven at 65 ± 3 °C for 48 h. After maceration, the specimens were washed (2-3 times) in distilled water and then immersed in distilled water. Then the shacked and the biometric parameters fiber length were evaluated by light microscopy. From each slice, at least 100 fibers were used for the measurements.

14Statistical analysis. This study involved conducting a statistical analysis using SPSS software (version 25). A one-way analysis of variance (ANOVA) was performed to assess significant differences between Pinus species for each anatomical parameter. When ANOVA indicated statistically significant differences (p < 0.05), post hoc comparisons of means were carried out using Tukey's honestly significant (Tukey HSD) test.

3. RESULTS

15Genomic DNA extraction from five Pinus samples revealed high molecular weight and comparable concentrations. The efficacy of DNA barcodes is contingent upon the efficiency of polymerase chain reaction (PCR) amplification and the accuracy of the primers employed. In this study, the rbcL marker exhibited a 100% success rate in amplification (around 900 bp). Table 1 presents the species identified by the rbcL barcode primer in the BLAST search, along with their respective accession numbers, and compares them with the taxonomist's identification. The results indicate a high degree of similarity among the Pinus strains, with most samples producing sequences classified as 99-98%. Moreover, the results illustrate a robust correlation between morphological and molecular identification at the genus level using this marker.

3.1. Genetic diversity analysis

16The study aimed to gain insight into the genetic diversity of pine species by summarizing the genetic diversity observed in the rbcL marker across five sequences. Twenty-three segregating sites were identified, as shown in tables 2 and 3. Visual inspection of the alignment revealed that these polymorphic sites were clustered in specific regions, particularly at positions 3-9, 425-462, and 879-885. Additionally, specific sites, such as positions 427, 428, 431, 443, and 446, exhibited unique nucleotide states for sequence E, and position 879 was unique for sequence D. These 23 segregating sites yielded a comparatively high nucleotide diversity (π) of 0.0137. The Tajima's D test yielded a value of 0.780, suggesting the potential for positive selection, population expansion, or purifying selection. Haplotype diversity (Hd) was calculated as 1.0. All five sampled Pinus sequences represent unique haplotypes, suggesting a high degree of haplotypic variation within this limited sample.

3.2. Phylogenetic tree analysis of rbcL barcoding gene

17The phylogenetic tree (Figure 3) was constructed using maximum likelihood methods from sequences retrieved from NCBI. It illustrates the evolutionary relationships among various Pinus species based on chloroplast genome regions, primarily the rbcL gene. All analyzed sequences demonstrated homology, indicating that they derived from a common ancestral gene or chloroplast region across the diverse Pinus species included.

Figure 3. A phylogenetic analysis of Pinus species based on rbcL gene sequences - Une analyse phylogénétique des espèces de Pinus basée sur les séquences du gène rbcL.

18The P. heldreichii cluster is supported by multiple accessions, including FR831914.1, DQ353730.1, AB019821.1, MT238042.1, and JN854195.1, which form cluster closely together, suggesting minimal genetic differences among them. Similar patterns of limited intraspecific variation are observed within the P. brutia (e.g., MT238028.1 and AB019820.1) and P. pinea (FN689374.1 and DQ353729.1) clades. Pinus pinea samples, including accessions FN689374.1, DQ353729.1, X58133.1, MT238064.1, JN854173.1, and NC_039585.1, cluster together, indicating a close evolutionary relationship. Pinus halepensis (JN854197.1) forms a distinct lineage. The P. brutia samples (MT238028.1, AB019820.1, FR831903.1, and JN854224.1) form another well-defined clade. Pinus crassicorticea (NC_041150.1) is identified as a distinct lineage as well. These samples with other Pinus species, such as P. tabuliformis var. henryi (MW537664.1), P. massoniana (MW537596.1, MW537616.1), and P. latteri (JN854190.1), show distinct evolutionary relationships. The grouping of P. heldreichii, P. pinea, P. halepensis, P. brutia, and P. crassicorticea suggests species-specific monophyly. The configuration of the phylogenetic tree is determined by bootstrap values, which indicate the percentage of iterations that support the tree at specific divergence points. As the number of iterations supporting the tree at a given divergence point increases, confidence in the tree's configuration increases.

3.3. Wood anatomy

19Table 4 shows the mean values of the anatomical characteristics of wood. Wood is characterized by an anatomical structure consisting of several elements which, in their system of arrangement, are responsible for many of wood natural and mechanical properties. There is also a variation in the shape, size, and proportion of these elements between wood species, and some of them, making the anatomical arrangement one of the means used to distinguish and define wood species (Figure 4).

Figure 4. Wood anatomy of Pinus species – Anatomie du bois des espèces de Pinus.

a. cross section – section transversale; b. longitudinal radial section – section longitudinale radiale; c. longitudinal tangential section – section longitudinale tangentielle.

3.4. Cross section

20The results of the cross-sectional study of coniferous wood species showed significant differences between the species in the following characteristics:

21– tracheal wall thickness µ (TWT): the high significant differences in the values of TWT were 39.2, 36.9, and 34.0 µ in P. halepensis, P. massoniana var. massoniana, and P. pinea, respectively. Furthermore, the value of TWT in P. heldreichii was 27.8 µ, while the lowest values of TWT were 20.3 µ in P. brutia;

22– latewood thickness: it was estimated as a percentage of the annual ring width. The results showed a highly significant difference (p < 0.05) between species: P. pinea and P. brutia had the highest percentages at 45.6% and 44.0% respectively, while P. massoniana var. massoniana had the lowest at 28.4%;

23– ray parenchyma area: the results showed no significant differences in values between the species;

24– resin ducts (%): significant differences were observed in the percentage of resin ducts relative to the cross-sectional area among the studied species. Pinus brutia had the lowest percentage (0.37%), whereas P. massoniana var. massoniana had the greatest (1.18%). At the same time, resin duct diameter varied significantly between species, with P. massoniana var. massoniana having the largest diameter (172.3 µ) and P. pinea having the smallest (112.4 µ);

25– number of resin ducts: the results showed highly significant differences between the species, where the highest number of resin ducts was in P. massoniana var. massoniana, while the lowest number was in P. brutia;

26– longitudinal radial section: the results showed highly significant differences between species for the characteristic of parenchyma ray height and number of cells. The highest value was observed in P. halepensis at 223 µ (12 cells), whereas P. pinea showed the lowest at 80.6 µ (5 cells), highlighting the significance of this difference;

27– longitudinal tangential section: the results of the number of uniseriate rays in 1 cm² area showed a highly significant difference between the species values, with the highest number in P. heldreichii (86) and the lowest in P. halepensis (49). This difference may be due to the relationship between age and the number of rays, where an inverse relationship is observed between the number of rays and age.

28– fiber length: the results of the fiber length of the Pinus species showed that there is a significant difference in the fiber length between the species, as the P. massoniana var. massoniana was characterized by the longest fibers (3.21 mm), while P. pinea had the shortest (2.37 mm).

4. DISCUSSION

29This study demonstrated the use of DNA barcoding for Pinus species identification as a complement to anatomical identification. To find discrepancies between anatomical and DNA identification results, sequences were cross-referenced with morphological identification and compared with GenBank reference sequences. Our results showed that about 60% of the samples were correctly recognized at the species level, although all valid identifications were made at the genus level. Genetic divergence highlights the importance of species identification. DNA barcoding is useful, especially for samples unidentifiable morphologically (Kress, 2017; Dormontt et al., 2018; Antil et al., 2023). Successful barcoding relies on strong morphological identification and comprehensive databases (Bell et al., 2017; Meiklejohn et al., 2019). This technique becomes important for biodiversity assessment and conservation, particularly in diverse regions lacking taxonomic expertise or detailed floristic descriptions (Hebert et al., 2003).

30The chloroplast rbcL gene has been a foundational DNA barcode marker since early phylogenetic reconstructions (Chase et al., 1993), gaining widespread use for species identification across diverse plant groups (Guo et al., 2015; Kaplan-Levy et al., 2015; Hadi et al., 2016). With over 50,000 sequences in databases (Bell et al., 2017; Omonhinmin et al., 2022), rbcLs are key advantages, particularly for Pinus species where morphological variation complicates taxonomy (Armenise et al., 2012; Giovannelli, 2017). The Consortium for Barcode of Life (CBOL) recognizes rbcL as a universal plant barcode (Antil et al., 2023). Phylogenetic studies reveal most Pinus species belong to Ponderosae, Oocarpae, Contortae, Australes, and Sabinianae lineages. The clades like Australes and Ponderosae share common ancestry (Singh et al., 2021). Researchers using rbcL and other genes found close relationships among North and Central American Pinus species (Gernandt et al., 2005; Hernández-León et al., 2013). Significant genetic diversity in exotic and native Pinus was observed in height, cone width, and seed characteristics (Singh & Thapliyal, 2012).

31Genetic diversity varies among Pinus species and populations. Some, like Scots pine, show high diversity, while others, such as P. pinea, exhibit remarkably low variability, hinting at complex evolutionary paths (Tani et al., 1996; Zhang et al., 2005; Vendramin et al., 2007; Kim et al., 2010; Sheller et al., 2023). The high genetic diversity observed in Chinese pine (Pinus tabuliformis Carrière) and Henry's pine (Pinus henryi Mast.) is due to habitat requirements and historical demographic processes (Li et al., 2008; Liu et al., 2012). Our phylogenetic analysis, based on rbcL sequences, supports the monophyly of the genus Pinus. This finding is consistent with the results of more comprehensive, multi-locus studies that have also robustly supported the monophyly of the genus using a combination of different barcode regions (Wang et al.,1999). The tree identifies two major clades, which are consistent with previous studies. The close relationship between P. heldreichii and P. pinea is further supported by Toromani et al. (2015). However, the long-branch attraction artifact observed for P. pinea in clade 2 suggests that additional molecular markers or more advanced phylogenetic methods may be needed to fully resolve the relationships within this clade. Future studies could incorporate a broader sampling of Pinus species and explore the potential role of hybridization and introgression in shaping the evolution of this genus. Based on this phylogeny, we can infer that: P. heldreichii, P. pinea, and P. brutia share a recent common ancestor and are more closely related to each other than to other Pinus species in the tree. Pinus halepensis and P. brutia are also closely related, suggesting a recent divergence. The percentage of bases in the genus Pinus, especially G+C (43.18%), is significantly lower than that of A+T (56.72%). Studies have shown similar G+C and A+T base percentages (Gernandt et al., 2005; Rinaldi & Sukarjo, 2022).

32Despite the use of multiple DNA barcodes, accurately identifying all Pinus species remains challenging (Monnet et al., 2021). Thus, a sequential approach, beginning with anatomical and concluding with molecular identification, can precisely determine Pinus wood species. The wood anatomy of the pine species exhibits distinct traits that can be used to identify and classify them. The physical contrasts among these species propose changing variations to their surroundings, especially considering dry season and environment changeability. Pinus halepensis and P. brutia show differentiating reactions to water accessibility, impacting their development and survival. These findings were similar to those reported by Panetsos et al. (1997) and Houminer et al. (2022). However, the dispersal of the axial tissue is important. Pinus massoniana var. massoniana has more articulated parenchyma tissue clusters than P. pinea.

33Understanding the morphological and anatomical characteristics of tree species is fundamental to their classification and conservation. Wood anatomical parameters are valuable for identification, provenance analysis, and ecological studies because they distinguish species and reflect environmental responses (Schweingruber, 2007; Martín et al., 2010). Our study examined traits such as tracheid wall thickness and ray parenchyma area in five Pinus species from Al-Jabal Al-Akhdar, and the results reinforce the utility of these traits for species differentiation. Combining these anatomical distinctions with molecular rbcL barcoding data provides a comprehensive picture of Pinus diversity in Libya. While anatomical traits can overlap, integrating rbcL barcoding data provides a more precise method for discriminating between species. Furthermore, recognizing that wood anatomical traits can exhibit site-related variation (Martín et al., 2010), our sampling strategy across different altitudes in the Al-Jabal Al-Akhdar region aimed to capture a broad representation of the species' natural diversity. This acknowledges the potential influence of local environmental conditions on these parameters. Understanding these physical characteristics is essential in the timber trade, as they affect the wood quality and its suitability for different applications. Comprehensive chloroplast genome studies (Ni et al., 2017) have highlighted the complex phylogenetic relationships within Pinus. This underscores the need for further research using a multi-locus approach to fully resolve the genus and develop a reliable system for species identification. Therefore, future strategies are expected to provide a more robust genetic framework by using multiple barcode regions in addition to rbcL, such as matK or ITS. This approach enhances the precision of species classification by utilizing additional genetic markers, which can reveal more detailed evolutionary connections among species. As a result, researchers can gain insights into the complexities of biodiversity and evolutionary history.

5. CONCLUSIONS

34The results provide further evidence that rbcL, a plant nuclear barcode, is capable of successfully identifying a wide variety of plant species. These results showed that the sample from Al-Jabal Al-Akhadar region of eastern Libya is most likely a Pinus species, as highlighted by both anatomical and genetic studies. To adapt and survive, Pinus species often maintain moderate to high levels of genetic variation. However, the distribution of this diversity varies between species and groups for a variety of reasons, including historical events, human activities, and geographic isolation. To formulate effective management plans for pine species, it is imperative to employ species-specific conservation methods and to leverage complementary techniques such as genetic diversity assessment, ecological niche modeling, and population demographic inference.

35Conflict of interest

36The authors declare that they have no conflict of interest.

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